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RESEARCH PRODUCT

Docking and multivariate methods to explore HIV-1 drug-resistance: a comparative analysis

Marco TutoneAntonino LauriaAnna Maria Almerico

subject

Models MolecularMultivariate statisticsMultivariate analysisAnti-HIV AgentsCombined useHuman immunodeficiency virus (HIV)Computational biologyDrug resistanceBiologyLigandsBioinformaticsmedicine.disease_causeHIV ProteaseMolecular descriptorDrug Resistance ViralDrug DiscoverymedicineHumansDOCKINGPhysical and Theoretical ChemistryBinding SitesHIV Protease InhibitorsSettore CHIM/08 - Chimica FarmaceuticaHIV Reverse TranscriptaseComputer Science ApplicationsDRUG RESISTANCEDocking (molecular)Drug DesignMultivariate AnalysisMutationHIV-1Computer-Aided DesignReverse Transcriptase InhibitorsMultivariate statistical

description

In this paper we describe a comparative analysis between multivariate and docking methods in the study of the drug resistance to the reverse transcriptase and the protease inhibitors. In our early papers we developed a simple but efficient method to evaluate the features of compounds that are less likely to trigger resistance or are effective against mutant HIV strains, using the multivariate statistical procedures PCA and DA. In the attempt to create a more solid background for the prediction of susceptibility or resistance, we carried out a comparative analysis between our previous multivariate approach and molecular docking study. The intent of this paper is not only to find further support to the results obtained by the combined use of PCA and DA, but also to evidence the structural features, in terms of molecular descriptors, similarity, and energetic contributions, derived from docking, which can account for the arising of drug-resistance against mutant strains.

yearjournalcountryeditionlanguage
2007-08-02Journal of Computer-Aided Molecular Design
https://doi.org/10.1007/s10822-008-9186-7